As the Internet age continues to grow, it is becoming more and more important for businesses to compile and analyze data regarding traffic on network servers. Web analytics programs for collecting and analyzing such data. One particular program available that is useful for web analytics is described in U.S. Pat. Nos. 6,112,238; 6,317,787; 6,925,442; and 7,185,085, which are incorporated by reference herein in their entirety.
With such current web analytics programs, there are two main approaches to collecting the server data. One approach is log file analysis that is the examination of log files in which the server records all of its transactions. The other approach is page tagging in which JavaScript® is utilized to notify a third-party server when a page is rendered by a web browser. The programs compile the data and reports may be generated to display information about web server activity, such as general statistics, most requested pages, least requested pages, most downloaded files, activity level by day of week, activity level by hour, bandwidth, page not found (404) errors, server errors, referring sites, referring URLs, search engines, search phrases, browsers or platforms, visiting spiders, most-used platforms and operating systems, etc.
The amount of data that is collected on a network server may be immense, especially for servers that support high network traffic. Thus, the generation of periodic reports (for example, daily reports, weekly reports, etc.) that compiles all the data may be a daunting task. The problem is magnified when technical personnel must produce one or more periodic reports for a plurality of different servers.
One of the problems associated with current web analytics programs is that in the retrieving of data and creation of various reports for a multitude of servers, it is difficult to assess the “health” of the server and/or web analytics program to anticipate and prevent potential problems in collecting the data and generating reports. Indeed, oftentimes the web analytics program may encounter problems that slow or stall the collection of data/generation of reports; however, the problems may not be recognized and/or rectified until after-the-fact and data may be lost or the client may be unable to view a particular periodic report until a later time than desired. As such, a need currently exists for a monitoring tool useful to assess the health of servers and/or the web analytics program during data processing.